Information Transmission Chapter 3, image and video OVE EDFORS - - PowerPoint PPT Presentation

Information Transmission Chapter 3, image and video

OVE EDFORS ELECTRICAL AND INFORMATION TECHNOLOGY

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Learning outcomes

Understanding

–

raster image formats and what determines quality,

–

video formats and what determines quality, and

–

the basics of image and video compression.

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Where are we in the BIG PICTURE?

WE'RE STILL HERE ... … AND A LITTLE BIT HERE.

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Images

• An image is a two-dimensional array of light values.
• Make it 1D by scanning
• Smallest element of an image is called a pixel.
• Number of pixels per cm/inch gives the resolution of the

image.

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Resolution

• Resolution of, e.g., a printer is in dots per inch (DPI).

Each dot is represented by a bit.

• 300 DPI – 12 dots/mm
• When the dots have different levels of grey, the image is

said to be of gray scale. Usually, 256 gray levels are used, so that each pixel is represented by 8-bits

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Example, 90, 300, 600 DPI

1 mm

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Display resolutions

Source: Wikipedia

In book: PAL In book: HDTV What you can buy today: 4K

Source: Wikipedia

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Images

• Representing color images requires specifying the

intensities Red, Green and Blue (RGB) colors.

• Digital images require huge memory for storage.
• Sophisticated image compression schemes like JPEG are

employed to reduce the size of images.

• These schemes employ the properties of images and the

behavior or response of human eye to reduce redundancy.

9 Let's zoom in!

10 Doesn't look as nice in close-up.

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Image formats

• Vector formats (e.g. SVG, EPS)

– Specify where lines should be drawn

• Raster format (e.g. TIFF/JPEG/PNG/GIF/BMP)

– Specify each pixel value (RGB) – May use different levels of compression

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Picture formats (original+5x magn.)

Bad jpeg Eps vector format png Good jpeg

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JPEG encoding

• The representation of the colors is converted from RGB to

Y′CBCR, consisting of one luma component (Y') for brightness, and two chroma components, (CB and CR), for color.

• The resolution of the chroma data is reduced. This

reflects the fact that the eye is less sensitive to fine color details than to fine brightness details.

• The image is split into blocks where each of the Y, CB,

and CR data undergoes the Discrete Cosine Transform, similar to a Fourier transform.

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JPEG encoding

• The amplitudes of the frequency components are
• quantized. Human vision is much more sensitive to small

variations in color or brightness over large areas than to the strength of high-frequency brightness variations.

• The magnitudes of the high-frequency components are

stored with a lower accuracy than the low-frequency

• components. If an excessively low quality setting is used,

the high-frequency components are discarded altogether.

• The resulting data for all blocks is further compressed

with a lossless algorithm.

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Fourier (cosine) transform of an image?

• Represent the

image by its frequency components

• Linear combination
• f the squares

here

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Einstein in the frequency domain

2D Fourier Transform

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Video

• Video is a continuously changing image or a sequence of

still images to give an impression of motion.

• Human eye suffers (or benefits?) from persistence of

vision.

• An image persists for about 60ms; if next image comes

before this time, it appears to be continuous.

• Also eye averages out the noise in successive images thus

boosting the effective SNR.

• These features are used to advantage in TV/video

transmission.

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Rasters in video

• To generate a TV signal, the TV screen or raster is

scanned at a very high rate.

• In the PAL system, a frame rate of 25 frames/second is

used to scan the raster. This yields a maximum bandwidth

• f 6.5 MHz for the TV signal, a bandwidth of 1-2 MHz

provides satisfactory picture quality.

• An SNR of 20 dB is sufficient for the video signal.
• Digital video signals have very high bit rates 60 Mbps.

Hence video compression algorithms like MPEG are widely employed that bring down to 2-5 Mbps

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HDTV

• High Definition TV: Increasing the number of scan lines

and increasing the analog bandwidth (50 MHz), thereby increasing the resolution.

• Sophisticated video compression schemes bring down

the bit rates to 10-20 Mbps. This allows transmission of HDTV signal in the same frequency channel used by analog TV (6-7 MHz)

• MPEG-2 Video compression standard includes the HDTV

apart from standard TV.

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Video compression

• The sequence of images contains spatial and temporal

redundancy that video compression algorithms attempt to eliminate or code in a smaller size.

• Only small differences between successive images.

– Use differential encoding: transfer/store differences

• Objects move or change

– shift, rotate, lighten, or darken

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History of video compression standards

Year Standard Publisher Popular Implementations 1984 H.120 ITU-T 1988 H.261 ITU-T Videoconferencing, Videotelephony 1993 MPEG-1 Part 2 ISO, IEC Video-CD 1995 H.262/MPEG-2 Part 2 ISO, IEC, ITU-T DVD Video, Blu-ray, Digital Video Broadcasting, SVCD 1996 H.263 ITU-T Videoconferencing, Videotelephony, Video on Mobile Phones (3GP) 1999 MPEG-4 Part 2 ISO, IEC Video on Internet (DivX, Xvid ...) 2003 H.264/MPEG-4 AVC Sony, Panasonic, ISO, Samsung, IEC, ITU-T Blu-ray, HD DVD Digital Video Broadcasting, iPod Video, Apple TV, 2006 VC-1 SMPTE Blu-ray, video on Internet 2009 VC-2 (Dirac) SMPTE Video on Internet, HDTV broadcast, UHDTV 2013 H.265 ISO, IEC, ITU-T High Efficiency Video Coding 2018 AV1 Alliance for Open Media HTML5 Video

Source: Wikipedia

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DVB-T2 (Digital Video Broadcasting –T2)

Digital Modulation Lines Frame rate Data rate

• CH. B/W

(MHz) COFDM (4/16/64/ 256 QAM) 1080 up to 50p Up to 50.34 Mbit/s 1.7, 5, 6, 7, 8,

• r 10

Video Coding Audio Coding Interactive TV Digital subchannels Single- Frequency Network H.264, H.262 MPEG-1 Layer II, HE-AAC yes Yes Yes

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SUMMARY

• (Raster) Image:

–

A 2D signal or array of color/light values

–

Smallest element called a pixel

–

Resolution often given in pixels/inch (PPI) or dots/inch (DPI)

–

Three component colors (typically RED, GREEN, BLUE) are required for color images.

• Video:

–

Sequence of images (frames)

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Frame rate based on human persistence of vision

• Compression methods:

–

Based on properties of images and human visual system

–

Can reduce storage size considerably